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Natural Language Processing with TensorFlow

You're reading from   Natural Language Processing with TensorFlow The definitive NLP book to implement the most sought-after machine learning models and tasks

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781838641351
Length 514 pages
Edition 2nd Edition
Languages
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Author (1):
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Thushan Ganegedara Thushan Ganegedara
Author Profile Icon Thushan Ganegedara
Thushan Ganegedara
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Table of Contents (15) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Understanding TensorFlow 2 3. Word2vec – Learning Word Embeddings 4. Advanced Word Vector Algorithms 5. Sentence Classification with Convolutional Neural Networks 6. Recurrent Neural Networks 7. Understanding Long Short-Term Memory Networks 8. Applications of LSTM – Generating Text 9. Sequence-to-Sequence Learning – Neural Machine Translation 10. Transformers 11. Image Captioning with Transformers 12. Other Books You May Enjoy
13. Index
Appendix A: Mathematical Foundations and Advanced TensorFlow

An intuitive understanding of Word2vec – an approach to learning word representation

“You shall know a word by the company it keeps.”

– J.R. Firth

This statement, uttered by J. R. Firth in 1957, lies at the very foundation of Word2vec, as Word2vec techniques use the context of a given word to learn its semantics.

Word2vec is a groundbreaking approach that allows computers to learn the meaning of words without any human intervention. Also, Word2vec learns numerical representations of words by looking at the words surrounding a given word.

We can test the correctness of the preceding quote by imagining a real-world scenario. Imagine you are sitting an exam and you find this sentence in your first question: “Mary is a very stubborn child. Her pervicacious nature always gets her in trouble.” Now, unless you are very clever, you might not know what pervicacious means. In such a situation, you automatically will be...

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